sustainability
Article
The Effect of Environmental, Social and Governance
Consistency on Economic Results
Idoya Ferrero-Ferrero *, María Ángeles Fernández-Izquierdo and María Jesús Muñoz-Torres
Finance and Accounting Deparment, Universitat Jaume I, 12071 Castellón de la Plana, Spain;
afernand@uji.es (M.Á.F.-I.); munoz@uji.es (M.J.M.-T.)
* Correspondence: Ferrero@uji.es; Tel.: +34-964-387-143
Academic Editor: Giuseppe Ioppolo
Received: 29 July 2016; Accepted: 21 September 2016; Published: 9 October 2016
Abstract: This study aims to explore how environmental, social and governance (ESG) consistency
impacts the firm performance, specifically, the relationship between ESG performance and economic
performance (EP). This study posits that the company’s commitment and effectiveness towards the
creation of consistent competitive advantage in environmental, social and governance dimensions
constitutes an intangible value that leads improvements in corporate performance. This work
uses a panel dataset for listed firms of the EU-15 countries during the period 2002 to 2011 and
applies Generalized method of moments (GMM) estimator system in order to address the potential
unobserved heterogeneity and dynamic endogeneity. The main results reveal that the global effect of
ESG performance on EP for those firms that present interdimensional consistency is greater than the
rest, except for higher levels of ESG performance.
Keywords: firm performance; economic performance; environmental; social and governance
performance; consistency; synergistic effect; generalized method of moments; endogeneity problems
1. Introduction
In recent years, the severity of the global financial crisis, its negative implications for growth
and development, the effects of climate change and the corporate scandals around the globe, have
increased the stakeholder interest in environmental, social and governance (ESG) concerns. On the
one hand, investors [1] and international organizations [2,3] have placed particular emphasis on the
critical role of companies towards contributing to sustainable development. On the other hand, taking
into account the expectations of a broad range of stakeholders—consumers, investors, policy-makers,
media, and NGOs—companies are showing a more proactive attitude to integrate ESG aspects in
the management system, which theoretically brings benefits in terms of corporate reputation, trust,
customer loyalty, cost savings, access to capital, human resource management, innovation capacity,
and risk management. In this sense, ESG performance is used by the stock market as a proxy of
company’s integration of corporate social responsibility (CSR) in corporate strategy.
In the academic world, after decades of research on the relationship between CSR and corporate
economic performance (EP), many scholars still claim that much research remains to be conducted
before this relationship can be fully understood, specifically developing models that incorporate
omitted variables [4–6]. In this regard, this study attempts to contribute to the literature gap of how
the combination of the ESG aspects in the management systems impacts on the firm performance [7]
by including the synergistic effect of the three ESG dimensions in the abovementioned relationship.
In order to test ESG synergistic effect, this study proposes the “interdimensional consistency” between
ESG dimensions and explores how this consistency can affect the relationship between ESG and EP.
This study contributes to the literature and business practices in different ways. Firstly, this study
advances to the emerging literature about consistency by exploring how the interrelationships
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across environmental, social and governance dimensions impacts on firm performance as a whole.
Secondly, this study develops different measures of consistency based on strengths in ESG dimensions
comparing the firms’ scores respect to their peer groups. Thirdly, it proposes three different levels
of ESG consistency to measure the company’s commitment and effectiveness towards the creation
of a competitive advantage. Fourthly, in terms of methodology, this paper uses a panel dataset for
listed firms of the EU-15 countries during the period 2002 to 2011 and applies generalized method of
moments (GMM) estimator system in order to address the potential unobserved heterogeneity and
dynamic endogeneity. And finally, this study reveals that those companies that obtain an excellent ESG
performance, there are not necessarily firms that outperform their competitors in all the extra-financial
performance dimensions. This result means that not all the excellent ESG companies maintain
an interdimensional consistency but they can offset strengths in some dimensions with weaknesses
in others.
This work is divided into five sections. After this introduction, Section 2 presents a literature
review and the hypotheses. Section 3 includes information on the sample, variables, and the
methodology used in estimating the models. Section 4 presents the results and Section 5 offers
the main conclusion.
2. Literature Review and Hypotheses
In the field of strategic management, the stakeholder theory [8] provides a reasoned perspective
on how firms should manage their relationships with stakeholders to ensure a sustainable corporate
success [9]. In particular, the instrumental stakeholder theory [10] assumes that the stakeholder
management practices can result in significant competitive advantage, minimizing costs and improving
economic performance. In this regard, a large number of authors [9,11–14] argue that those firms that
integrate environmental, social and governance factors into management can create and maintain
value for their stakeholders by providing better products and services, attracting and retaining
higher quality employees, enhancing the company’s reputation, increasing customer loyalty, gaining
social legitimacy and improving risk management among others. Likewise, from the resource-based
perspective [15,16], those firms with strong extra-financial capabilities (e.g., environmental ones)
improve the organizational process to efficiently and competitively use of tangible and intangible
assets boosting their capacity for generating economic results.
A broad range of empirical studies have tested the relationship between various types of
social and environmental performance and economic performance. A substantial proportion of
empirical studies reported positive effects of social and/or environmental performance on economic
performance [4,17–20], while others found a mixed relationship [21], no significant effects [22] or
negative effects [23]. In this regard, a recent meta-analysis [24] that combines the findings of about
2200 studies shows that a vast majority of studies reported a positive relationship between ESG
dimensions and financial performance. Based on such arguments and the recent meta-analysis results,
this study establishes the following baseline hypothesis:
Hypothesis 1. The level of ESG performance is positively associated with economic performance.
A possible explanation of the mix findings in the ESG-EP relationship could be that previous
research has omitted the interactions between different ESG dimensions and their moderating
effects [16,25]. To measure ESG performance, many previous studies have been based on a rating
that includes different dimensions. However, a particular level of a rating can conceal different levels
of uniformity in the ESG dimensions, which can affect the economic performance. In this respect,
the concept of “uniformity” is closely related to “consistency”, which reflects an imperative to maintain
coherence in the diverse and complex businesses and in the relations with the environments [26].
In the literature, the concept of consistency has been explored from different perspectives. As Soda
and Zaheer [27] state, the organizational research emphasizes the value of consistency among organisztional
elements, arguing that internal fit among them enhances corporate performance, maintaining a coherence
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image of the organization and creating value through the mutual reinforcement between and
within tangible and intangible assets of the organization. From a managerial firm perspective,
strategic consistency implies an alignment among stakeholder approach of companies, their declared
commitments, and their performance [28].
Recently, a stream of the empirical literature on CSR has included the concept of “consistency” to
explore the relationship between social and environmental performance and financial performance.
Moneva et al. [28] analyzed whether the strategic consistency of the firm related to its stakeholders
led to successful financial results. For that end, the authors developed an index to measure the
degree of strategic consistency between the sustainability reporting—external transparency—and the
strategic orientation of the firm—internal level. The main result revealed that those companies with
a strategic stakeholder consistency commitment did not achieve lower financial performance than
those organizations with a shareholder approach. Oikonomou et al. [26], focusing on intradimensional
CSR consistency, investigated how the corporate financial performance was affected by the impacts
of uniformly positive, uniformly negative and mixed—positive and negative—indicators in five
dimensions—community, diversity, employee, environment, and product. They found evidence
that firms, that exhibited uniformly positive or negative indicators in particular dimensions of CSR,
outperformed firms that showed a mixed picture of positive and negative indicators, suggesting
stakeholders’ judgments of CSR reward uniformity. Likewise, Wang and Choi [29], considering the
same five dimensions of Oikonomou et al. [26], examined temporal and interdomain consistency in
CSR. Temporal consistency refers to the reliability of a firm’s treatment of its stakeholders over time,
while interdomain consistency indicates uniformity in a firm’s treatment of its different stakeholder
groups. Wang and Choi [29] concluded that the two types of consistency in CSR interact positively to
influence a firm’s financial performance.
This study contributes to literature by proposing the “interdimensional consistency” based on the
organizational and management literature. The interdimensional consistency is defined as a balanced
approach, in a positive direction, among the environmental, social and governance dimensions.
The interdimensional consistency is aligned with the concept of “strong sustainability”, which allows
a lower degree of tolerance to offset economic, social and environmental pillars [30,31]. In this regard,
the offsetting effect cannot be accepted when good results in one dimension may hide the absence of
results or inadequacy of policies in other dimensions [32–34].
This study explores how the interrelationships across environmental, social and governance
dimensions impacts on firm performance as a whole. In particular, this study attempts to fill
the research gap of the consistency based on strengths in ESG dimensions depending on its peer
groups. Recent research has documented an increasingly strong lateral effect of CSR on the strategic
management, which represents a pressure generated by the corporate community itself [35]. In this
regard, Barnett [36] explains that in an industry when a company engage in misconduct or when the
industry as a whole is perceived as lacking social or environmental awareness, some companies invest
extra efforts and resource to adopt CSR as an integral component of corporate strategy with the aim
of differentiating from their less responsible colleagues and being positively judged by the market
actors. These efforts can build competitive advantage and provide extra economic performance for
synergistic reasons. In contrast, those companies that do not increase their CSR practices to match the
competitors in their industry may have significant losses of reputation and customer loyalty, causing
economic harm.
Theoretically, the different dimensions of the corporate ESG performances are interdependent.
On the one hand, whether a company maintains a high degree of consistency of strengths may develop
different value chain activities aligned with the acquired commitments, increasing the social complexity
of a company’s relationship assets, encouraging that the corporate behavior are in harmony with the
environment, and improving the strategic management process. In this regard, the interaction value of
the different ESG practices exceeds the total value of individual and isolated efforts, creating a strong
ESG strategy, which cannot easily be mimicked by competitors. In this vein, Wagner [37] states that
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sustainability integration, determined by the different stakeholder domains, is a mediator variable
between stakeholder demands and corporate performance, since sustainability integration aligns the
environmental and social objective with other strategic ones and ensures that activities and projects
are not in conflict, capturing the simultaneous influence of stakeholders.
On the other hand, according to Wang and Choi [29], those firms that present ESG performance
relationships built without consistency, will not develop a strong ESG strategy and will be easier for
competitors to replicate it. To reflect these arguments, this study tests the following hypothesis:
Hypothesis 2. The interdimensional consistency affects positively to the effect of the ESG performance on
economic performance.
3. Research Methodology
3.1. Sample Selection
The sample consists of those companies listed in the stock exchanges of the EU-15 member states
for the period 2002–2011 that report ESG data in Asset4 database. This study explores EU-15 members
given the potential differences across regions in the ESG-EP relations [24]. The analyzed time series
finish in 2011 due to the structural changes promoted by the “renewed EU strategy 2011–2014 for
Corporate Social Responsibility” [38]. This strategy could have generated a mediating effect exerted
by CSR national policies from EU countries after 2012. The starting point of the sample includes data
from 506 firms and 3809 firm-year observations. This study uses a lag-structure for the dependent
variable based on previous research [16,39]. This structure results in a loss of observations related
to a specific year, 2002. In addition, this study deleted those firms with missing data in a particular
year, since it could generate inconsistent estimations. Taking into account these conditions, the final
sample of the study includes 460 firms and 3071 firm-year observations. However, with the aim of
applying a robust dynamic approach, those firms that did not present the ESG scores for four or less
years, were in a first stage not considered. This restricted sample consists of an unbalanced panel of
373 firms and 2835 firm-year observations since 87 firms do not have sufficient ESG data over time to
meet the latter criterion. Nonetheless, the results also were checked in the non-restricted unbalanced
panel in order to address the ESG disclosure bias.
The information was obtained from Thomson Reuters Asset4 database, which uses only publicly
available information. As Schäfer et al. [40] state, Thomson Reuters Asset4 database provides
transparent, objective, auditable, comparable and systematic economic, environmental, social and
governance information, offering a comprehensive platform for establishing benchmarks for the
assessment of corporate performance. Thomson Reuters Asset4 contains over 250 key performance
indicators organized into 18 categories within four dimensions: (1) economic performance score;
(2) social performance score; (3) environment performance score; and (4) corporate governance score.
Note that all firms from Luxemburg were deleted because the database did not contain the information
about ESG for their firms.
3.2. Variables
The dependent variable is the economic dimension (ECONOMIC) that is measured using the
economic performance score provided by Thomson Reuters Asset4. This score measures a company’s
capacity to generate sustainable growth and a high return on investment through the efficient use of
all its financial and non-financial resources, building on the research gap found by Goyal et al. [41].
This proxy is the reflection of a company’s overall financial health and its ability to generate long-term
profits. Economic performance data is presented relative to a representative group of the industry,
which is measured by the median [42,43]. According other studies [14,44], the industry is defined by
Standard Industrial Classification (SIC) codes. This study uses one-digit SIC code given the sample
size and the scale used to define the relative measures. Therefore, the ECONOMIC variable is defined
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as the difference between a firm’s score and the median of the ECONOMIC scores across all listed firms
in the same one-digit SIC and from the country in which the company is registered in a particular year.
With respect to the independent variables, this study includes two extra-financial variables: (i) the level
of ESG performance (ESG); and (ii) the interdimensional ESG consistency (INTERDIMENSIONAL
CONSISTENCY). According to previous articles [45,46], this study measures the level of ESG
performance for every year and each firm, constructing a composite index with equal weights
to each of the three dimensions: social, environmental, and corporate governance. This variable
allows testing Hypothesis 1. Regarding the interdimensional ESG consistency, this study builds three
different levels of ESG consistency based on strengths in ESG dimensions. In this study, a strength
means that a firm performs over or equal its peer group in environmental, social or governance
terms. In order to identify strengths, this study explores the categories related to each extra-financial
dimension. In particular, Thomson Reuters Asset4 structures the environmental dimension in three
categories—resource reduction, emission reduction, and product innovation—the social dimension
in seven categories—human rights, workforce opportunity, society and community, training and
development, product responsibility, employment quality, and health and safety—and corporate
governance dimension in five categories—vision and strategy, shareholder rights, board functions,
board structure, and compensation policy. In line with previous research [47–50], this study uses the
median as a measure of central tendency of performance which represents a group level indicator
for each category in a given industry, country and year and allow identifying those firms that have
strengths—if are over or equal the media. In this regard, Liden et al. [47] used the median to explore the
effects of leader-member exchange differentiation on individual and group performance. Kim et al. [48]
defined the ethical behavior of borrowers and lenders depending whether the business ethics scores
were above or below the median value of the distribution for the corresponding sector and year.
Tang and Luo [49] measured the extent of the carbon pollution mitigation taking into account whether
the firm’s emissions intensity was lower than the median of its sector, since this measure is more
comparable across firms than data based on absolute emissions. Likewise, Laroche and Salesina [50]
used a dummy variable on the bases of the samples’ median to identify those firms that made the most
and least intensive use of high performance work practices.
This study uses seven dummy variables to identify those firms that have a position over or equal
the median respect to the industry in all categories for each dimension, for two specific dimensions
or for the three dimensions. Table 1 shows the description of each dummy variable. In this regard,
the first level of ESG consistency, the dummy variables only identify the firms that have strengths
in all the categories of each dimensions in an independent way and, actually, they show consistency
within each dimension and they do not represent any type of interdimensional consistency. The second
level represents bidimensional consistency, which is understood as the uniformity in the performance
position regarding all the categories associated with two extra-financial dimensions. For instance,
a firm presents environmental and social consistency whether it performs better (or equal) in both
dimensions with respect to the peer group, regardless of its position in corporate governance dimension.
Based on the indicator of strength for each dimension, this study builds a new set of dummy variables
to identify those firms that jointly presents strengths in two dimensions. The third level corresponds to
the interdimensional ESG consistency, which is associated with Hypothesis 2.
This study uses a dummy variable to identify those firms that have strengths in the three dimensions.
With the aim of testing asymmetries in the ESG-EP relationship depending on the interdimensional
consistency, this study multiplies the dummy variables above-mentioned by ESG performance.
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Table 1. Dummy variables to identify the different levels of interdimensional consistency.
Type of Consistency
Dummy Variable
First level of consistency.
It considers consistency within each
dimension in an independent way.
Second level of consistency.
Bidimensional consistency.
Third level of consistency.
Interdimensional ESG consistency.
Description
CONSISTENCYE
The performance of the environmental categories is above or
equal to the median of the reference group.
CONSISTENCYS
The performance of the social categories is above or equal to the
median of the reference group.
CONSISTENCYG
The performance of the corporate governance categories is above
or equal to the median of the reference group.
CONSISTENCYES
The performance of the environmental and social categories is
above or equal to the median of the reference group.
CONSISTENCYSG
The performance of the social and corporate governance
categories is above or equal to the median of the reference group.
CONSISTENCYEG
The performance of the environmental and corporate governance
categories is above or equal to the median of the reference group.
CONSISTENCYESG
The performance of the environmental, social and corporate
governance categories is above or equal to the median of the
reference group.
Focusing on control variables and consistent with previous empirical research [14,51,52], the firm
specific variables that could affect the economic performance are: the natural log of total assets as
an indicator for size (SIZE); capital expenditures divided by total assets as proxy for investment ratio
(CAPEX); total debt per unit of total assets as a proxy for capital structure (LEVERAGE); and annual
growth rate of sales as indicator of growth (GROWTH). Additionally, as Muhammad et al. [53]
state the relationship between environmental performance and financial performance depends on
the macroeconomic context: growth or contraction period. In this regard, a dummy variable is
created to differentiate the periods before and after the 2007 financial crash (YEARS CRISIS). Financial
industry plays an important role in the economic development and their industrial peculiarities such as
self-regulation—e.g., Equator Principles—or explicit economic benefits from outside sources—e.g.,
public funds to bailout distressed financial institutions—may affect their economic performance [39,54].
For these reasons, this study includes an additional dummy variable in order to reflect differences
between finance and insurance industry (FINANCIAL INDUSTRY) and the rest of industries.
For addressing the idiosyncrasy among regions according to their legal system, this study uses
the Zattoni and Cuomo [55] criterion to classify countries according to the legal origin system
(ENGLISH SYSTEM) (FRENCH SYSTEM) (GERMAN SYSTEM) (SCANDINAVIAN SYSTEM). In this
case, the omitted dummy is the one for countries with a legal system based on the English law tradition.
Moreover, this study includes the dependent variable lagged by one period (ECONOMICt−1 ) with the
aim to capture the existence of some inertia in economic performance year after year.
3.3. Model and Method
In order to test the hypotheses, this study estimates the linear regression models presented in
Equation (1).
ECONOMICi,t
=
+
+
+
β0 + β1 × ECONOMICi,t-1 + β 2 × ESGi,t + β3 × I NTERDI MENSION AL CONSISTENCY i,t
β4 × SIZEi,t + β5 × CAPEX i,t + β6 × GROWTH i,t + β7 × LEVERAGEi,t + β8 × YEARS CRISISt
β9 × FRENCH SYSTEMi,t + β10 × GERMAN SYSTEMi,t + β11 × SCANDI N AV I AN SYSTEMi,t
β12 × FI N ANCI AL I NDSUTRY i,t + η i + νit
(1)
Consistent with previous research [18,56], Equation (1) contains economic performance as the
dependent variable, which is explained by ESG performance, interdimensional ESG consistency and
control variables. The “Interdimensional Consistency” variable specified in Equation (1) is divided
into different variables that reflect the strengths in the ESG dimensions and allow testing the effect of
interdimensional consistency on economic performance presented in Hypothesis 2. This study tests
the hypotheses by regressing 8 models because the joint estimation of the interaction variables presents
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problems of collinearity. Table 2 displays the consistency variables included in each model and their
purpose. The problem collinearity has been explored by means of the variance inflation factors (VIF)
for the independent variables. The VIF values in the different models are below 10 except for variables
with interaction terms, but, in this case, multicollinearity should not be a significant concern [57].
Given the feature of the data (cross-sectional and time-series data), this study uses the panel
data methodology. In this case, it is necessary to consider the existence of latent unobservable effects
specific to each firm (η i ). Moreover, the variables used in this research may present endogeneity
problems. Wooldridge [58] suggests that the general approach for estimating models that present
problems of endogeneity is the use of instruments. In this regard, an instrumental variable approach is
applied to address the endogeneity problem; in particular, the system-GMM estimator proposed by
Arellano and Bover [59] and Blundell and Bond [60]. This estimator also addresses the presence of
unobserved heterogeneity since it transforms the variables into first differences. This estimator has
been implemented using a two-step methodology, since the estimates are efficient and asymptotically
robust in the presence of heteroscedasticity.
Table 2. Consistency variables included in each model and their purpose.
Model
Model 1 (Baseline)
Variables Included in
“Interdimensional Consistency”
-
Types of Consistency Included in the Model and Their Purpose
Without interdimensional ESG consistency.
It allows knowing the coefficient associated with ESG before including
interdimensional ESG consistency.
CONSISTENCYESG
Model 2
CONSISTENCYESG x ESG
CONSISTENCYE
Model 3
CONSISTENCYE x ESG
CONSISTENCYS
Model 4
CONSISTENCYS x ESG
CONSISTENCYG
Model 5
CONSISTENCYG x ESG
CONSISTENCYES
Model 6
CONSISTENCYES x ESG
Third level of interaction variables: interdimensional ESG consistency.
It allows knowing the effect of the interdimensional ESG consistency on
economic performance.
First level of interaction variables, considering strengths for the
environmental dimension.
It allows knowing the effect of being consistent within environmental dimension
on the ESG-EP relationship
First level of interaction variables, considering strengths for the social dimension.
It allows knowing the effect of being consistent within social dimension on the
ESG-EP relationship.
First level of interaction variables, considering strengths for the corporate
governance dimension.
It allows knowing the effect of being consistent within corporate governance
dimension on the ESG-EP relationship.
Second level of interaction variables: bidimensional consistency between
environmental and social dimensions.
It allows knowing the effect of being consistent within and between environmental
and social dimensions on the ESG-EP relationship.
CONSISTENCYSG
Second level of interaction variables: bidimensional consistency between social
and governance dimensions.
CONSISTENCYSG x ESG
It allows knowing the effect of being consistent within and between social and
corporate governance dimensions on the ESG-EP relationship.
Model 7
CONSISTENCYEG
Model 8
CONSISTENCYEG x ESG
Second level of interaction variables: bidimensional consistency between
environmental and corporate governance dimensions.
It allows knowing the effect of being consistent within and between environmental
and corporate governance dimensions on the ESG-EP relationship.
4. Empirical Results and Discussion
Table 3 shows the descriptive statistics and a correlation matrix for the main variables.
All variables of consistency are correlated with the level of economic performance. The variables that
consider strengths in Environmental, Social, or Governance terms present a positive relationship with
EP and ESG performance. Another preliminary result of the correlation matrix is that the economic
performance presents the strongest correlation with respect to environmental dimension and the
weakest correlation with respect to corporate governance.
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Table 3. Descriptive Statistics and Correlation Matrix.
Variable
(1) ECO
(2) ESG
(3) CONSISTENCYE
(4) CONSISTENCYE x ESG
(5) CONSISTENCYS
(6) CONSISTENCYS x ESG
(7) CONSISTENCYG
(8) CONSISTENCYG x ESG
(9) CONSISTENCYES
(10) CONSISTENCYES x ESG
(11) CONSISTENCYSG
(12) CONSISTENCYSG x ESG
(13) CONSISTENCYEG
(14) CONSISTENCYEG x ESG
(15) CONSISTENCYESG
(16) CONSISTENCYESG x ESG
(17) SIZE
(18) CAPEX
(19) GROWTH
(20) LEVERAGE
Mean S.D.
−0.43
56.43
0.38
25.14
0.19
12.28
0.15
9.46
0.16
10.41
0.10
5.74
0.12
7.43
0.09
5.27
15.19
6.52
0.92
63.27
18.83
18.75
0.49
33.85
0.39
26.56
0.36
23.53
0.37
24.87
0.30
18.45
0.33
21.24
0.29
17.71
2.14
12.58
37.98
23.34
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
(13)
(14)
(15)
(16)
(17)
(18)
(19)
0.46 ***
0.33 ***
0.37 ***
0.25 ***
0.28 ***
0.13 ***
0.16 ***
0.22 ***
0.25 ***
0.10 ***
0.12 ***
0.11 ***
0.13 ***
0.08 ***
0.11 ***
0.30 ***
−0.03 †
−0.01
0.12 ***
0.41 ***
0.57 ***
0.20 ***
0.33 ***
0.12 ***
0.25 ***
0.18 ***
0.30 ***
0.03 ***
0.14 ***
0.10 ***
0.22 ***
0.02 ***
0.13 ***
0.39 ***
−0.07 ***
−0.04 *
0.16 ***
0.95 ***
0.47 ***
0.45 ***
0.36 ***
0.34 ***
0.56 ***
0.54 ***
0.38 ***
0.35 ***
0.47 ***
0.45 ***
0.41 ***
0.38 ***
0.30 ***
−0.05 *
0.01
0.14 ***
0.42 ***
0.47 ***
0.29 ***
0.34 ***
0.51 ***
0.55 ***
0.28 ***
0.32 ***
0.40 ***
0.44 ***
0.30 ***
0.35 ***
0.36 ***
−0.04 *
0.00
0.15 ***
0.95 ***
0.49 ***
0.43 ***
0.91 ***
0.86 ***
0.68 ***
0.64 ***
0.54 ***
0.46 ***
0.65 ***
0.61 ***
0.20 ***
−0.00
0.03 †
0.09 ***
0.40 ***
0.41 ***
0.86 ***
0.91 ***
0.57 ***
0.62 ***
0.44 ***
0.44 ***
0.54 ***
0.59 ***
0.26 ***
−0.01
−0.01
0.11 ***
0.95 ***
0.50 ***
0.41 ***
0.78 ***
0.73 ***
0.87 ***
0.82 ***
0.75 ***
0.70 ***
0.09 ***
−0.01
0.03 *
0.02
0.43 ***
0.42 ***
0.68 ***
0.73 ***
0.82 ***
0.87 ***
0.65 ***
0.70 ***
0.15 ***
−0.01
0.01
0.04 *
0.95 ***
0.69 ***
0.64 ***
0.60 ***
0.52 ***
0.72 ***
0.68 ***
0.19 ***
0.00
0.03 †
0.08 ***
0.57 ***
0.61 ***
0.50 ***
0.50 ***
0.60 ***
0.65 ***
0.25 ***
0.00
0.01
0.10 ***
0.94 ***
0.82 ***
0.72 ***
0.96 ***
0.90 ***
0.05 **
0.02
0.05 **
0.00
0.76 ***
0.76 ***
0.90 ***
0.95 ***
0.11 ***
0.02
0.03
0.02
0.94 ***
0.86 ***
0.80 ***
0.07 ***
0.01
0.04 *
0.02
0.75 ***
0.80 ***
0.13 ***
0.00
0.02
0.04 *
0.94 ***
0.03 *
0.02
0.05 **
−0.01
0.10 ***
0.02
0.03
0.01
−0.17 ***
−0.01
0.37 ***
−0.01
−0.11 ***
−0.02
The table shows the descriptive statistics and the correlation of the data included in the unbalanced panel (full sample).
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001.
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Tables 4–6 present the eight models regressed in this study. Model 1 (Table 4) presents the
baseline model, which does not include any indicator of ESG consistency. In line with the results
of a large number of studies [17–19], a positive relationship is evident between the level of ESG
performance and economic performance (0.4253, p-value < 0.001). This relationship remains positive
and highly significant when the ESG consistency is included in the model (Models 2–8). Therefore,
this result supports the Hypothesis 1 “The level of ESG performance is positively associated with
economic performance”.
Table 4. Estimates of the ESG—Economic performance relationship: Baseline and ESG consistency.
Dependent Variable: ECONOMICi,t
Model (1)
Model (2)
ECONOMICi,t−1
0.2741 ***
(0.0258)
0.2656 ***
(0.0252)
ESGi ,t
0.4253 ***
(0.0258)
0.4338 ***
(0.0483)
CONSISTENCYESGi ,t
-
13.0526 ***
(3.7814)
CONSISTENCYESGi ,t x ESGi ,t
-
−0.1694 **
(0.0570)
SIZEi ,t
0.7029
(0.4898)
0.7903
(0.4893)
CAPEXi ,t
0.0647
(0.0410)
0.0675
(0.0417)
GROWTHi ,t
0.0207
(0.0180)
0.0030
(0.0208)
LEVERAGEi ,t
−0.1453 *
(0.0570)
−0.1424 †
(0.0555)
YEARS CRISISt
−3.991 ***
(0.5853)
−3.8460 ***
(0.5930)
FRENCH SYSTEMi ,t
−2.5434 *
(1.2097)
−3.0410 *
(1.2541)
GERMAN SYSTEMi ,t
0.9871
(1.6328)
−0.4287
(1.6833)
SCANDINAVIAN SYSTEMi ,t
−2.4834
(1.7571)
−2.7067
(1.8282)
FINANCIAL INDUSTRYi ,t
3.0646 *
(1.3768)
3.4496 *
(1.4064)
CONSTANT
−23.5841 ***
(4.3249)
−25.8262 ***
(4.4804)
Wald test
414.19 ***
424.25 ***
2835
2835
360.59
368.62
−10.93 ***
−10.94 ***
1.58
1.53
N. obs.
Hansen test
χ2
AR1
AR2
The table reports the two-step GMM system estimator.
errors are in brackets.
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001. Standard
Model 2 (Table 4) reflects the interdimensional ESG consistency, by means of two indicators:
CONSISTENCYESG, which represents those firms that have all the performance of the extra-financial
categories above or equal the median of the reference group; and CONSISTENCYESG x ESG,
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which denotes the combination of ESG performance and those firms that are over or equal the median
in all the categories associated with environmental, social and governance dimensions. The coefficient
of the variable CONSISTENCYESG is significant and with the expected sign. However, the variable
CONSISTENCYESG x ESG is significant but with an opposite sign, which means that the marginal
effect of ESG performance on EP is positive but is lower when a firm is consistent in all categories
of the three dimensions: environmental, social and corporate governance (0.4338–0.1694, p < 0.01),
than a firm that shows mixed or lower performance in some or all extra-financial categories to their
peers (0.4338, p < 0.001). This result does not support Hypothesis 2 “The interdimensional consistency
affects positively to the effect of the ESG performance on economic performance”.
Models 3–5 (Table 5) consider the first level of ESG consistency, i.e., the strengths within each ESG
dimension. The results show that the coefficients of the consistency variables are not significant for the
environmental dimension. Regarding social and corporate governance dimensions, the marginal effect
of ESG performance on EP is lower for those firms that offer a consistency within social dimension
and corporate governance dimension independently. The marginal effect is given by the coefficient
(0.4252–0.1067, p < 0.10) for those firms that have the performance of all their social categories over
or equal their peers and by the coefficient (0.4541–0.1303, p < 0.05) for those firms that have the
performance of all their corporate governance categories over or equal their peers.
Models 6–8 (Table 6) take into account the bidimensional consistency. In the second level of
consistency, for those firms that present jointly strengths in social and environmental dimensions
(Model 6) the finding reveals that there are not significant differences for the marginal effect of
ESG performance on EP than for the rest of firms. However, focusing on consistency between
social and corporate governance dimensions, Model 7 shows that those firms that present social
and corporate governance bidimensional consistency have a lower impact (0.4496–0.1903, p < 0.05)
of ESG performance on economic performance than the rest. A similar result is obtained when
environmental and corporate governance bidimensional consistency is explored. Model 8 displays
a lower effect (0.4554–0.2015, p < 0.001) of ESG performance on economic performance for those
firms that have better or equal results in all categories associated with environmental and corporate
governance dimensions.
Consequently, the results obtained exploring consistency in the three levels—third level of
consistency: Model 2; second level of consistency: Models 6–8; and first level of consistency: Models
3–5—do not support Hypothesis 2. Note that these outcomes do not mean that the market actors do
not appreciate interdimensional consistency, since the dummy variable coefficient, when significant,
is always positive. Considering also the interaction variable, the global effect of ESG on EP for those
firms that present interdimensional consistency is greater than the rest, except for the higher levels of
ESG performance. A possible explanation of this outcome is that ESG initiatives and performance may
differ in their visibility, allowing firms to offset strategically. In this regard, Torres et al. [61] showed
that local social responsibility policies in communities generate brand value and foster the positive
effect of corporate social responsibility toward other stakeholders, particularly customers. In line with
this argument, those firms that concentrate their efforts to be leaders on those extra-financial categories
that have the greatest visibility may increase the effectiveness of ESG practices to stakeholders and
credibility to the firm, obtaining better economic performance than those firms that intends to stand
equal or above their peers in all the extra-financial categories.
Additionally, another possible argument could be that the market interest in nonfinancial
information differs depending on the analyzed dimension and within each dimension. In this sense,
Eccles and Serafeim [62] examined the interest of professional investors in 247 nonfinancial metrics
included in Bloomberg database and they concluded that, at the aggregate market level, interest in
environmental information was greater than in social one, due to the greater concern about climate
change and the fact that environmental issues are easier to quantify and integrate into valuation
models. Regarding corporate governance dimension, professional investors were mainly interested
in the principles of good governance, which are associated to traditional board characteristics such
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as percentage and number of independent directors, size of the board, or CEO duality, becoming
other governance aspects related to environmental and social dimensions, for example “Executive
Compensations linked to ESG”, less important.
Table 5. Estimates of the ESG—Economic performance relationship: ESG interdimensional consistency.
Dependent Variable: ECONOMICi ,t
Model (3)
Model (4)
Model (5)
ECONOMICi,t−1
0.2698 ***
−0.0246
0.2681 ***
−0.0259
0.2655 ***
−0.026
ESGi ,t
0.4045 ***
−0.0548
0.4252 ***
−0.0513
0.4541 ***
−0.0488
CONSISTENCYEi ,t
3.5913
−3.0205
-
-
CONSISTENCYEi ,t x ESGi ,t
−0.024
−0.0472
-
-
CONSISTENCYSi ,t
-
10.3122 *
−4.5797
-
CONSISTENCYSi ,t x ESGi ,t
-
−0.1067 †
−0.0623
-
CONSISTENCYGi ,t
-
-
9.5119 *
−3.9022
CONSISTENCYGi ,t x ESGi ,t
-
-
−0.1303 *
−0.0562
SIZEi ,t
0.7451
−0.4731
0.7151
−0.5096
0.7079
−0.4613
CAPEXi ,t
0.0621
−0.0412
0.0606
−0.0419
0.0677 †
−0.0411
GROWTHi ,t
0.0159
−0.0201
0.0034
−0.0185
0.0091
−0.0197
LEVERAGEi ,t
−0.1520 **
−0.0541
−0.1478 **
−0.0553
−0.1460 **
−0.0535
YEARS CRISISt
−3.8576 ***
−0.5946
−3.7566 ***
−0.5874
−3.9819 ***
−0.5824
FRENCH SYSTEMi ,t
−2.8272 *
−1.2287
−3.2257 **
−1.2308
−2.6246 *
−1.26
GERMAN SYSTEMi ,t
0.5122
−1.5919
0.2034
−1.6048
0.4062
−1.5449
SCANDINAVIAN SYSTEMi ,t
−2.8280 †
−1.7186
−2.8541
−1.8105
−2.5931
−1.7939
FINANCIAL INDUSTRYi ,t
2.9252 *
−1.4231
3.3089 *
−1.455
3.6052 **
−1.3696
CONSTANT
−23.1980 ***
−4.4135
−24.0442 ***
−4.6122
−25.4061 ***
−4.408
Wald test
421.78 ***
428.51 ***
443.48 ***
2835
2835
2835
363.96
367.21
363.54
−11.04 ***
−10.95 ***
−10.84 ***
1.64
1.54
1.48
N. obs.
Hansen test
AR1
χ2
AR2
The table reports the two-step GMM system estimator.
errors are in brackets.
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001. Standard
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Table 6. Estimates of the ESG—Economic performance relationship: Bidimensional consistency and
ESG interdimensional consistency.
Dependent Variable: ECONOMICi,t
Model (6)
Model (7)
Model (8)
ECONOMICi,t−1
0.2694 ***
−0.0252
0.2644 ***
−0.0253
0.2660 ***
−0.0254
ESGi,t
0.4052 ***
−0.0492
0.4496 ***
−0.049
0.4554 ***
−0.0508
CONSISTENCYESi ,t
6.4106 *
−3.1688
-
-
CONSISTENCYESi ,t x ESGi ,t
−0.0632
−0.0447
-
-
CONSISTENCYSGi ,t
-
15.6871 **
−5.8407
-
CONSISTENCYSGi ,t x ESGi ,t
-
−0.1903 *
−0.0783
-
CONSISTENCYEGi ,t
-
-
14.2274 ***
−3.5328
CONSISTENCYEGi ,t x ESGi ,t
-
-
−0.2015 ***
−0.05
SIZEi ,t
0.7904
−0.4949
0.758
−0.4977
0.6554
−0.467
CAPEXi ,t
0.0583
−0.0408
0.0683
−0.0412
0.0687 †
−0.0415
GROWTHi ,t
0.0088
−0.019
−0.0017
−0.0197
0.0079
−0.0207
LEVERAGEi ,t
−0.1382 *
−0.0547
−0.1433 **
−0.0521
−0.1354 **
−0.051
YEARS CRISISt
−3.7141 ***
−0.5826
−3.8328 ***
−0.6046
−3.9166 ***
−0.5875
FRENCH SYSTEMi ,t
−3.1206 *
−1.2541
−3.256 *
−1.2735
−2.7700 *
−1.286
GERMAN SYSTEMi,t
0.0721
−1.6318
0.0992
−1.6959
0.437
−1.7054
SCANDINAVIAN SYSTEMi,t
−2.8372
−1.8315
−2.7648
−1.7937
−2.4610 *
−1.7717
FINANCIAL INDUSTRYi,t
2.8600 *
−1.4032
3.6932 **
−1.4052
3.6105 *
−1.407
CONSTANT
−24.2197 ***
−4.3863
−26.2627 ***
−4.6106
−25.4296 ***
−4.5046
Wald test
385.95 ***
444.22 ***
414.21 ***
N. obs.
2835
2835
2835
366.53
362.47
368.76
−10.97 ***
−10.94 ***
−10.92 ***
1.57
1.47
1.52
Hansen test
AR1
χ2
AR2
The table reports the two-step GMM system estimator.
errors are in brackets.
†
p < 0.10; * p < 0.05; ** p < 0.01; *** p < 0.001. Standard
With respect to control variables, the leverage, the French legal system and the dummy that
contains the years of the financial crisis are statistically significant and negative related to the economic
performance. Regarding the industry dummy, those firms of the finance and insurance industry have
Sustainability 2016, 8, 1005
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a positive effect on economic performance. The rest of the control variables, i.e., firm size, invest ratio,
and growth rate of sales show the expected sign although they are not statistically significant.
To further check the robustness of the main results, this study has regressed Models 1–8 using full
sample. In this case, the results are available upon request from the authors. It is observed that the
coefficients and the level of significance have not changed substantially, thus the above-mentioned
findings are supported. In addition, this study reports the results of two specification tests in Tables 4–6:
the second—order serial correlation test (AR2) and the Hansen test of over-identification. The results
do not reject the validity of the Models 1–8 and the hypothesis that the instruments are valid.
5. Conclusions
Numerous studies have investigated the link between corporate social responsibility and economic
performance. A broad range of these studies have used a particular score of a corporate social
responsibility rating to measure social performance without considering the differences in the outcomes
among the dimensions. This study advances in the understanding of the ESG—economic performance
relationship, exploring the impact of interdimensional ESG consistency on this relationship. For that
end, this paper identifies those firms that present strengths in environmental, social and governance
dimension with respect to their peer groups and builds three different levels of ESG consistency:
(i) the first level does not represent any interdimensional consistency; (ii) the second level shows
bidimensional consistency; and (iii) the third level denotes interdimensional ESG consistency.
To test empirically the hypotheses, this paper uses a panel of listed firms from EU-15 during the
period 2002–2011 and applies the GMM estimator system, which addresses heterogeneity and
endogeneity problems.
The main finding reveals that those firms that have interdimensional consistency present a global
effect of ESG on EP greater than the rest, except for higher levels of ESG performance. This result
points out that market actors do not penalize the offsetting effect for those firms that concentrate their
efforts to be leaders on some extra-financial categories which allow them to obtain a noticeable good
result in the ESG rating as a whole.
This study has important implications for academics and practitioners. For academics, this
study proposes a new type of strategic and organizational consistency, “the interdimensional ESG
consistency”, and tests its effect on economic results. In addition, the paper encourages the use
of relative measures of economic and ESG performance based on the context—industry, year
and country—and applies these measures to identify those firms that present strengths in ESG
dimensions. For business practice, this study suggests that the consistency effect of extra-financial
dimensions on economic results could be conditioned by the market preferences, which are unbalanced
between environmental, social and governance dimensions and market actors do not penalize the
offsetting effect of the performance from different dimensions when the global ESG performance
is high. In this regard, public policy should change the approach of the normative and voluntary
guidelines towards the concept of “strong sustainability”, which allows a lower degree of tolerance
to compensate among the different extra-financial dimensions. This fact will allow market actors to
consider in their decision-making process the variable “interdimensional consistency” and to call into
question those firms that behind an excellent global ESG performance conceal weaknesses in some
extra-financial dimensions.
The findings of this empirical research should be viewed in light of potential limitations that
might open new areas for future research. A limitation of this study is that empirical findings are
conditioned by the sample and the availability of information. Samples with companies from other
regions are clearly needed to test the robustness of the results. The results of this study might
also be limited by the ESG rating and the models used. On the one hand, the ESG performance
variable could be enhanced by considering the market actor preferences [32] or adopting a lifecycle
approach. On the other hand, the modelization of the relationship between ESG-EP could be tested
Sustainability 2016, 8, 1005
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introducing inter-temporal effects [25], as well as inverted U-shape relationship between dependent
and independent variables [63].
The results of this paper may serve as a starting point for future research in strategic consistency,
examining how the interdimensional ESG consistency affects the economic value for the different
stakeholders, such as revenue and client loyalty or shareholder returns. This future study could
improve the knowledge on the individual stakeholder’s interests and their relationship with the
interdimensional ESG consistency.
Acknowledgments: The authors wish acknowledge the financial support received from P1•1B2013-31 and
P1•1B2013-48 projects through the Universitat Jaume I, and the Sustainability and Corporate Social Responsibility
Master Degree (UJI–UNED). The authors thank the anonymous reviewers for their insightful comments
and suggestions.
Author Contributions: This article is a joint work of the three authors. María Ángeles Fernádez-Izquierdo contributed
to research ideas, instruction, structure, and decision making aspects of this paper. María Jesús Muñoz-Torres
contributed to the analysis of the results and to write the paper. Idoya Ferrero-Ferrero contributed to data
collection and analysis and to write the paper. All other have read and approved the final manuscript.
Conflicts of Interest: The authors declare no conflict of interest.
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